CN109587051A - A kind of electric power terminal communication access net plan of operation method - Google Patents
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L45/00—Routing or path finding of packets in data switching networks
- H04L45/22—Alternate routing
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L45/00—Routing or path finding of packets in data switching networks
- H04L45/12—Shortest path evaluation
- H04L45/122—Shortest path evaluation by minimising distances, e.g. by selecting a route with minimum of number of hops
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Abstract
The invention belongs to electric power terminal communication access net technical fields, more particularly to a kind of electric power terminal communication access net plan of operation method, algorithm for design BuildPath (G (N, E), source, destination), the feasible path of business is taken by the operational authority gravity treatment on hop count and path, k item is chosen from feasible path selects the path of business weight distribution equilibrium as plan of operation path apart from shortest path alternately path, then from alternative path.The algorithm can effectively solve the problem that the problem of business is assembled to a small number of paths, to reduce business risk caused by path failure.
Description
Technical field
The invention belongs to electric power terminal communication access net technical fields, and in particular to a kind of electric power terminal communication access net industry
Business planing method.
Background technique
With the fast development of smart grid, more and more intelligent electric power terminals, sensor device, portable terminal quilt
Deployment in the power communication network, provides monitoring, control, information collection, intelligent power etc. for power grid operation person and user
The increasingly frequent feature of communication for coordination between numerous subsystems is presented in service, electric system.A large number of services needs to be deployed in network
It goes, how reasonably to plan electric power adapted telecommunication service path, reducing service communication risk becomes guarantee power system stability
One of major issue of operation.However, there are some problems for existing path planning algorithm, it is special for power communication to need design
Point service path planning algorithm.
Power communication department is main to consider the most short problem in path during service deployment, will lead to a large amount of electric power adapteds
The phenomenon that telecommunication business is assembled to several paths will lead to a large number of services interruption once these paths are broken down.Cause
This considers the harmonious problem of business weight distribution, can reduce during planning electric power adapted telecommunication service path
The risk that a large amount of electric power adapted telecommunication business are interrupted simultaneously, has important practical significance.
For the state of development for understanding the prior art, retrieval is carried out to existing paper and patent, has compared and analyzes, has been screened
It is related to the present invention as follows out to spend relatively high technical information:
Technical solution 1: " the electric power adapted telecommunication business based on blurring decision tree of Patent No. CN106022583A
Risk Calculation method and system " patent, it is related to a kind of electric power adapted telecommunication business risk calculating based on blurring decision tree
Method, main to be completed by seven steps: first, divided using operation flow of the analytic hierarchy process (AHP) to power communication system
Solution, establishes electric power adapted telecommunication business model layered；Second, determine the electric power layered established with electricity consumption
In communication service model at least two leaf nodes each leaf node risk indicator, and be at least two risk indicators
In each risk indicator determine weighted value；Third carries out consistency check at least two risk indicator and when logical
It crosses after consistency check using at least two risk indicator as input data；4th, by one in the input data
Divided data establishes training pattern as training data；5th, using another part data in the input data as test number
According to testing the training pattern；6th, when training pattern passes through test, using training pattern to input data into
Row classification, obtains classification results；7th, and classified calculating is carried out according to classification results to determine every kind of business in power communication
Value-at-risk.
Technical solution 2: a kind of " green electric power supply communication planning method " patent of Patent No. CN107346461A is related to one
Kind green electric power supply communication planning method, main to be completed by two steps: first, pass through PUE value evaluation data center's energy and imitates
Rate index judges the green degree height of data center, it is characterised in that, PUE index is generalized to communications equipment room, obtains one
Kind CT efficiency computation model；Second, plan new communication energy-saving switching network, data network and transmission network, replacement communications equipment room auxiliary
It equipment and introduces new management mode and passes through networking and facility are improved.
A kind of technical solution 3: " power telecom network planning side towards binary channels failure of Patent No. CN105610618A
Method " patent, it is related to a kind of power telecom network planing method towards binary channels failure, main to be completed by four steps: first,
Double service channels break down simultaneously in transmission net topology；Second, construct the optimization aim of network topology structure；Third solves
Optimize channel path；4th, building optimization structure.
The defect of the above-mentioned prior art:
Technical solution 1 is decomposed using operation flow of the analytic hierarchy process (AHP) to power communication system, establishes layered structure
Electric power adapted telecommunication business model；Determine each leaf in the electric power adapted telecommunication business model layered established
The risk indicator of child node, and weighted value is determined for risk indicator；Consistency inspection is carried out at least two risk indicator
It tests and after through consistency check using at least two risk indicator as input data；It will be in the input data
A part of data establish training pattern as training data；Using another part data in the input data as test number
According to testing the training pattern；When training pattern passes through test, input data is divided using training pattern
Class obtains classification results；And the value-at-risk of every kind of business in power communication is determined according to classification results progress classified calculating,
And this method also results in the phenomenon that business is assembled to a small number of paths according to value-at-risk smallest allocation path.
The invention discloses a kind of CT efficiency computation models for technical solution 2, and are surveyed according to technology trends and energy consumption
Try comparative analysis and related operating experience, it is proposed that a kind of green communications planing method.By to power communication ICT equipment energy consumption
With benefit integration test, it is quasi- to establish effective and feasible high energy consumption, poor benefit battery limits minute mark, is set to formulate green electric power supply communication
It is standby to network and logout specification, instruct communication system of power grids green to regenerate；By the research to the energy-saving strategy of power communication, effectively dig
It digs equipment potential, improve utilization rate of equipment and installations, promote Power Communication Resources and distribute ability rationally, reduce company investment cost, and be somebody's turn to do
Method does not account for path most short and service distribution factor.
It is same in double service channels to realize business in the case where most of network node degree are 3 by 3 present invention of technical solution
When failure under do not interrupt, the problem of effective solution power telecom network resists N-2 failure, and this method does not account for industry
The equiblibrium mass distribution problem for weight of being engaged in.
Summary of the invention
In order to solve the above technical problem, the present invention provides a kind of electric power terminal communication access net plan of operation methods, lead to
The operational authority gravity treatment crossed on hop count and path takes the feasible path of business, and k item is chosen from feasible path and is made apart from shortest path
For alternative path (distance is by business weight calculation), then from alternative path the path of business weight distribution equilibrium is selected as industry
Business planning path.The problem of algorithm can effectively solve the problem that, business is assembled to a small number of paths, to reduce caused by path failure
Business risk.
The invention is realized in this way a kind of electric power terminal communication access net plan of operation method, if G (N, E) is electric power
The topological structure of communication network, wherein N is the node collection of power telecom network, and E is the path set of power telecom network, algorithm for design
BuildPath (G (N, E), source, destination) for calculate node source and destination node destination it
Between service deployment path, in which:
K most neighbors by algorithm for design InitPath (source) for search node source, i.e., with
The node that hop count is 1 between source, if taking the smallest preceding k of business weight more than k；If taking reality less than k
Quantity, algorithm for design SelectNextNode (ni, C) and for screening k alternative path of business, algorithm for design SetService
(source, destination, P) from alternative path for selecting the path of business weight distribution equilibrium as service deployment
Path.
Further, algorithm BuildPath (G (N, E), source, destination) specifically comprises the following steps:
101) communication node n is seti∈ N, and set each communication node niOn business weight be the business weight carried thereon
Sum；
102) communication node n is setiWith communication node njBetween hop count jumpijFor most short hop count；
103) industry will be put into the smallest preceding k neighbors of node source hop count using algorithm InitPath (source)
It is engaged in set of paths A；
104) service path is calculated using algorithm SetService (source, destination, A), SetService's
Three parameters indicate that destination, A are as the starting point of service path, terminal and optional path set respectively with source；
105) set A and node source are put into set C, i.e. A ∪ { source } → C；
106) set A is deleted from G (N, E), i.e. G (N, E)/A → G (N, E)；
If 107) G (N, E) is not null set, i.e. G (N, E) ≠ φ goes to step 108, otherwise, terminates；
108) the nearest node n of distance source is found outi；
109) by niIt is deleted from G (N, E), i.e. G (N, E)/{ ni}→G(N,E)；
110) optional path set is searched for using algorithm SelectNextNode, by alternative path storage into set B, i.e.,
SelectNextNode(ni,C)→B；
111) if destination is in B or hop count jumpijEqual to α, i.e. (destination ∈ B) or
(jumpij=α), 112 are gone to step, otherwise, goes to step 114；
112) algorithm SetService (n is utilizedi, destination, B) and calculating service path, three of SetService
Parameter indicates respectively with ni, destination, B are as the starting point of service path, terminal and optional path set；
113)niIt is added in set C, i.e. C ∪ { ni} → C, goes to step 107；
If 114) jumpij< α goes to step 115, otherwise, goes to step 116；
115) hop count jumpijAdd 1, jumpij+1→jumpij, go to step 107；
116)niBusiness cannot be distributed, goes to step 107.
Further, algorithm InitPath (source) specifically comprises the following steps:
201) enabling set A is null set, i.e. φ → A, design number variable counter are 0, i.e. 0 → counter；
202) if each neighbors (being 1 node jumped to source) of source is traversed, 207 are gone to step, otherwise,
Go to step 203；
203) D is the neighbors collection of source；
If 204) D is not null set and counter is not 0, i.e. (D ≠ φ) ∩ (counter ≠ k) goes to step 5,
Otherwise, 7 are gone to step；
205) the nearest neighbors n of distance source is foundi；
206) by node niIt is put into set A, A ∪ { ni} → A, by node niIt is deleted from set D, i.e. D/ni→ D is counted
Variable counter adds 1, counter+1 → counter, goes to step 204；
207) A is returned.
Further, algorithm SelectNextNode (ni, C) specifically comprise the following steps:
301) enabling set S is null set, i.e. φ → S, hop count jump are 1, i.e. 1 → jump；
If 302) jump=α, 307 are gone to step, otherwise, goes to step 303；
303) n will be arrived in CiHop count be less than jump node njIt is put into A, i.e. nj→A；
304) by source to n in AiThe smallest preceding k paths P of hop countkIt is stored in set of paths B, i.e. Pk→B；
305) by source to n in CiThe minimum λ paths of business weight are put into set C, i.e. Pλ→C,λ∈[1,k]；
306) taking S is the union of S and C, i.e. S ∪ C → S, jump value is jump+1, i.e. jump+1 → jump is gone to step
302；
307) S is returned.
Further, algorithm SetService (source, destination, P) specifically comprises the following steps:
401) enabling set S is null set, i.e. φ → S；
If 402) traversed the path in P, the starting point in path is source, and terminal destination is gone to step
404, otherwise, go to step 403；
403) fromThe middle maximum node n of selection business weightiIt is put into set S, S ∪ { ni} → S, piFor in P
Path, go to step 402；
404) minimum n is selected from SminCorresponding path pmin, dispose business.
Compared with the prior art, the advantages of the present invention are as follows: this method divides electric power adapted telecommunication business weight balancing
Cloth is as target.Firstly, being service selection feasible path in the node that hop count is less than threshold value.Then, selection distance is minimum
K paths, the path candidate as business.Finally, selecting the path of business weight distribution equilibrium from alternative path, make
For traffic assignments path, to ensure the harmony of business weight distribution.Using method provided by the invention, electricity is effectively increased
The harmony of power adapted telecommunication business weight distribution, reduces path failure to the wind of electric power adapted telecommunication service constitution
Danger.
Detailed description of the invention
Fig. 1 is BuildPath (G (N, E), source, destination) algorithm flow chart；
Fig. 2 is InitPath (source) algorithm flow chart；
Fig. 3 is SelectNextNode (ni, C) and algorithm flow chart；
Fig. 4 is SetService (source, destination, P) algorithm flow chart；
Fig. 5 (a) is the weight distribution of deployed business in embodiment；
Fig. 5 (b) is the result that business is disposed according to shortest path first；
Fig. 5 (c) is the result that the method according to the invention disposes business.
Specific embodiment
In order to make the objectives, technical solutions, and advantages of the present invention clearer, with reference to the accompanying drawings and embodiments, right
The present invention is further elaborated.It should be appreciated that specific embodiment described herein is used only for explaining the present invention, and
It is not used in the restriction present invention.
In order to solve the problems in background technique, the present invention sets the topological structure that G (N, E) is power telecom network, and wherein N is
The node collection of power telecom network, E be power telecom network path set, algorithm for design BuildPath (G (N, E), source,
Destination) for the service deployment path between calculate node source and destination node destination, in which:
The k closest node of search node source is used for by algorithm for design InitPath (source), design to be calculated
Method SelectNextNode (ni, C) and for screening k alternative path of business, algorithm for design SetService (source,
Destination, P) for selecting the path of business weight distribution equilibrium as service deployment path from alternative path.
It is BuildPath (G (N, E), source, destination) algorithm flow chart with reference to Fig. 1, including walks as follows
It is rapid:
101) communication node n is seti∈ N, and set each communication node niOn business weight be the business weight carried thereon
Sum；
102) communication node n is setiWith communication node njBetween hop count jumpijFor most short hop count；
103) industry will be put into the smallest preceding k neighbors of node source hop count using algorithm InitPath (source)
It is engaged in set of paths A；
104) service path is calculated using algorithm SetService (source, destination, A), SetService's
Three parameters indicate that destination, A are as the starting point of service path, terminal and optional path set respectively with source；
105) set A and node source are put into set C, i.e. A ∪ { source } → C；
106) set A is deleted from G (N, E), i.e. G (N, E)/A → G (N, E)；
If 107) G (N, E) is not null set, i.e. G (N, E) ≠ φ goes to step 108, otherwise, terminates；
108) the nearest node n of distance source is found outi；
109) by niIt is deleted from G (N, E), i.e. G (N, E)/{ ni}→G(N,E)；
110) optional path set is searched for using algorithm SelectNextNode, by alternative path storage into set B, i.e.,
SelectNextNode(ni,C)→B；
111) if destination is in B or hop count jumpijEqual to α, i.e. (destination ∈ B) or
(jumpij=α), 112 are gone to step, otherwise, goes to step 114；
112) algorithm SetService (n is utilizedi, destination, B) and calculating service path, three of SetService
Parameter indicates respectively with ni, destination, B are as the starting point of service path, terminal and optional path set；
113)niIt is added in set C, i.e. C ∪ { ni} → C, goes to step 107；
If 114) jumpij< α goes to step 115, otherwise, goes to step 116；
115) hop count jumpijAdd 1, jumpij+1→jumpij, go to step 107；
116)niBusiness cannot be distributed, goes to step 107.
With reference to Fig. 2, it is InitPath (source) algorithm flow chart, includes the following steps:
201) enabling set A is null set, i.e. φ → A, design number variable counter are 0, i.e. 0 → counter；
202) if each neighbors (being 1 node jumped to source) of source is traversed, 207 are gone to step, otherwise,
Go to step 203；
203) D is the neighbors collection of source；
If 204) D is not null set and counter is not 0, i.e. (D ≠ φ) ∩ (counter ≠ k) is gone to step
205, otherwise, go to step 207；
205) the nearest neighbors n of distance source is foundi；
206) by node niIt is put into set A, A ∪ { ni} → A, by node niIt is deleted from set D, i.e. D/ni→ D is counted
Variable counter adds 1, counter+1 → counter, goes to step 204；
207) A is returned.
It is SelectNextNode (n with reference to Fig. 3i, C) and algorithm flow chart, include the following steps: (
301) enabling set S is null set, i.e. φ → S, hop count jump are 1, i.e. 1 → jump；
If 302) jump=α, 307 are gone to step, otherwise, goes to step 303；
303) n will be arrived in CiHop count be less than jump node njIt is put into A, i.e. nj→A；
304) by source to n in AiThe smallest preceding k paths P of hop countkIt is stored in set of paths B, i.e. Pk→B；
305) by source to n in CiThe minimum λ paths of business weight are put into set C, i.e. Pλ→C,λ∈[1,k]；
306) taking S is the union of S and C, i.e. S ∪ C → S, jump value is jump+1, i.e. jump+1 → jump is gone to step
302；
307) S is returned.
With reference to Fig. 4, it is SetService (source, destination, P) algorithm flow chart, includes the following steps:
401) enabling set S is null set, i.e. φ → S；
If 402) traversed the path in P, the starting point in path is source, and terminal destination is gone to step
404, otherwise, go to step 403；
403) fromThe middle maximum node n of selection business weightiIt is put into set S, S ∪ { ni} → S, piFor in P
Path, go to step 402；
404) minimum n is selected from SminCorresponding path pmin, dispose business.
With reference to Fig. 5 (a), Fig. 5 (b) and Fig. 5 (c), digital representation business weight on node, Fig. 5 (a) is deployed industry
The weight distribution of business, Fig. 5 (b) and Fig. 5 (c) are respectively to dispose according to shortest path first and BuildPath (G (N, E)) algorithm
Business as a result, the business weight distribution obtained according to the mentioned algorithm of this patent is more balanced.
Claims (5)
1. a kind of electric power terminal communication access net plan of operation method, which is characterized in that setting G (N, E) is opening up for power telecom network
Flutter structure, wherein N be power telecom network node collection, E be power telecom network path set, algorithm for design BuildPath (G (N,
), E source, destination) for the service deployment road between calculate node source and destination node destination
Diameter, in which:
K most neighbors by algorithm for design InitPath (source) for search node source, i.e., with source it
Between hop count be 1 node, if taking the smallest preceding k of business weight more than k；If taking actual quantity less than k, design
Algorithm SelectNextNode (ni, C) and for screening k alternative path of business, algorithm for design SetService (source,
Destination, P) for selecting the path of business weight distribution equilibrium as service deployment path from alternative path.
2. electric power terminal communication access net plan of operation method as described in claim 1, which is characterized in that algorithm
BuildPath (G (N, E), source, destination) specifically comprises the following steps:
101) communication node n is seti∈ N, and set each communication node niOn business weight be the business weight carried thereon
With；
102) communication node n is setiWith communication node njBetween hop count jumpijFor most short hop count；
103) business road will be put into the smallest preceding k neighbors of node source hop count using algorithm InitPath (source)
In diameter set A；
104) using algorithm SetService (source, destination, A) calculate service path, three of SetService
Parameter indicates that destination, A are as the starting point of service path, terminal and optional path set respectively with source；
105) set A and node source are put into set C, i.e. A ∪ { source } → C；
106) set A is deleted from G (N, E), i.e. G (N, E)/A → G (N, E)；
If 107) G (N, E) is not null set, i.e. G (N, E) ≠ φ goes to step 108, otherwise, terminates；
108) the nearest node n of distance source is found outi；
109) by niIt is deleted from G (N, E), i.e. G (N, E)/{ ni}→G(N,E)；
110) optional path set is searched for using algorithm SelectNextNode, by alternative path storage into set B, i.e.,
SelectNextNode(ni,C)→B；
111) if destination is in B or hop count jumpijEqual to α, i.e. (destination ∈ B) or (jumpij=
α), 112 are gone to step, otherwise, goes to step 114；
112) algorithm SetService (n is utilizedi, destination, B) and calculate service path, three parameters of SetService
It indicates respectively with ni, destination, B are as the starting point of service path, terminal and optional path set；
113)niIt is added in set C, i.e. C ∪ { ni} → C, goes to step 107；
If 114) jumpij< α goes to step 115, otherwise, goes to step 116；
115) hop count jumpijAdd 1, jumpij+1→jumpij, go to step 107；
116)niBusiness cannot be distributed, goes to step 107.
3. electric power terminal communication access net plan of operation method as claimed in claim 2, which is characterized in that algorithm InitPath
(source) specifically comprise the following steps:
201) enabling set A is null set, i.e. φ → A, design number variable counter are 0, i.e. 0 → counter；
202) if each neighbors (being 1 node jumped to source) of source is traversed, 207 are gone to step, otherwise, turns step
Rapid 203；
203) D is the neighbors collection of source；
If 204) D is not null set and counter is not 0, i.e. (D ≠ φ) ∩ (counter ≠ k) goes to step 205, no
Then, 202 are gone to step；
205) the nearest neighbors n of distance source is foundi；
206) by node niIt is put into set A, A ∪ { ni} → A, by node niIt is deleted from set D, i.e. D/ni→ D, counting variable
Counter adds 1, counter+1 → counter, goes to step 204；
207) A is returned.
4. electric power terminal communication access net plan of operation method as claimed in claim 2, which is characterized in that algorithm
SelectNextNode(ni, C) specifically comprise the following steps:
301) enabling set S is null set, i.e. φ → S, hop count jump are 1, i.e. 1 → jump；
If 302) jump=α, 307 are gone to step, otherwise, goes to step 303；
303) n will be arrived in CiHop count be less than jump node njIt is put into A, i.e. nj→A；
304) by source to n in AiThe smallest preceding k paths P of hop countkIt is stored in set of paths B, i.e. Pk→B；
305) by source to n in CiThe minimum λ paths of business weight are put into set C, i.e. Pλ→C,λ∈[1,k]；
306) taking S is the union of S and C, i.e. S ∪ C → S, jump value is jump+1, i.e. jump+1 → jump goes to step 302；
307) S is returned.
5. electric power terminal communication access net plan of operation method as claimed in claim 2, which is characterized in that algorithm
SetService (source, destination, P) specifically comprises the following steps:
401) enabling set S is null set, i.e. φ → S；
If 402) traversed the path in P, the starting point in path is source, terminal destination, goes to step 404, no
Then, 403 are gone to step；
403) fromThe middle maximum node n of selection business weightiIt is put into set S, S ∪ { ni} → S, piFor the road in P
Diameter goes to step 402；
404) minimum n is selected from SminCorresponding path pmin, dispose business.
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